The ultimate goal is to export that dataset into Excel.īut before you export that data, you’ll need to create a DataFrame in order to capture this information in Python. Let’s say that you have the following dataset about products and their prices: Product Then, the DataFrame will be exported to an Excel fileĮxample used to Export Pandas DataFrame to an Excel File.A DataFrame will be created from scratch.Excel will open a Power Query Editor window.
Double-click the file to connect it to Excel. Here, open the folder where your JSON file is located. You will see your computer’s standard Import window. In the next section, you’ll see a simple example, where: On the Data tab, from the Get & Transform Data section, select Get Data > From File > From JSON. You may then use PIP to install openpyxl as follows: pip install openpyxl ModuleNotFoundError: No module named ‘openpyxl’ Note: you’ll have to install openpyxl if you get the following error: Here is a template that you may apply in Python to export your DataFrame: df.to_excel(r'Path where the exported excel file will be stored\File Name.xlsx', index = False)Īnd if you want to export your DataFrame to a specific Excel Sheet, then you may use this template: df.to_excel(r'Path where the exported excel file will be stored\File Name.xlsx', sheet_name='Your sheet name', index = False) You can export Pandas DataFrame to an Excel file using to_excel.
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